用在线推断动态调控量子传感，确保结果可靠且精度高
Dynamic Estimation Loss Control in Variational Quantum Sensing via Online Conformal Inference
- 结合在线共形推断动态调整参数
- 在量子磁力计任务中实现长期可靠估计
- 适合追求高可靠性量子传感的科研人员
量子传感利用非经典效应突破经典传感器的局限，应用于引力波探测到纳米级成像。然而，基于噪声中等规模量子（NISQ）设备的实际量子传感器面临显著噪声和采样限制，现有变分量子传感（VQS）方法缺乏严格的性能保障。本文提出一种在线控制框架，动态更新变分参数的同时提供估计值的确定性误差范围。通过在线共形推断技术，该方法生成具有保证长期风险水平的序列估计集。在量子磁力计任务中的实验表明，所提动态VQS方法在长时间运行中保持所需可靠性，同时仍能获得精确估计。结果证明，将变分量子算法与在线共形推断结合，可在NISQ设备上实现可靠的量子传感。
原文摘要 · Abstract (English)
Quantum sensing exploits non-classical effects to overcome limitations of classical sensors, with applications ranging from gravitational-wave detection to nanoscale imaging. However, practical quantum sensors built on noisy intermediate-scale quantum (NISQ) devices face significant noise and sampling constraints, and current variational quantum sensing (VQS) methods lack rigorous performance guarantees. This paper proposes an online control framework for VQS that dynamically updates the variational parameters while providing deterministic error bars on the estimates. By leveraging online conformal inference techniques, the approach produces sequential estimation sets with a guaranteed long-term risk level. Experiments on a quantum magnetometry task confirm that the proposed dynamic VQS approach maintains the required reliability over time, while still yielding precise estimates. The results demonstrate the practical benefits of combining variational quantum algorithms with online conformal inference to achieve reliable quantum sensing on NISQ devices.
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